The smartphone became an important and indispensable part of our daily life, and its usage has been extended to a large number of applications that covers each and every need of our life. Although the smartphone has many benefits to our society, it has also some negative impacts such as driver destruction. The usage of the smartphone by the driver while driving either for call conversations, texting or just web navigation is extremely dangerous as a large number of road accidents are caused by the driver being distracted by its smartphone.
To overcome with this negative side of the technology (smartphone), many solutions have been introduced to the market to mainly disable the smartphone while driving. The simplest solutions rely on the driving speed to look the smartphone i.e. if the smartphone knows that it is moving faster than a defined maximum speed e.g. by using the embedded GPS, it lock the smartphone and disable all the possible destruction functionalities on the smartphone. If the smartphone is used by a passenger and not a driver it should not be unlocked, but the simple solution which is purely based on the movement speed does unfortunately not distinguish whether the smartphone is used by the driver or just a passenger.
To distinguish the driver user from the passenger user, in-vehicle localization has been introduced in some solutions. Such in-vehicle localization solutions use external extra solutions such as Bluetooth or sound emitters to be installed inside the vehicles. These in-vehicles localization solutions provide a localization of the smartphone inside the vehicle but with a level of accuracy which is not enough to distinguish the driver from the passenger when the smartphone is physically located on or near the borders between the driver area and the passengers area.
Further, localization and route guidance are an important part of many applications that are used in a daily basis. There are mainly two categories of localization technologies. The first category includes satellite-based systems like GPS and which can be used in outdoor areas that are under the coverage of the related satellites. The second category includes proximity and short-range wireless or light sensing technologies that are often used to enable localization inside indoor environment where the first category cannot be used due to the unavailability of the satellite coverage. The first category above relies on pre-deployed satellites that provide coverage through large areas around the globe, and these satellites are already deployed and can be used from anywhere as long as they are seen from the target area. Unfortunately the satellite-based localization systems cannot be used to enable indoor localization, and here the second category above comes to overcome and enable indoor-localization. These second category systems provide accurate localization as long as the target system is fine-tuned in advance to a system (set of sensors) pre-installed in the target area. Therefore, the second category fails when it comes to non-pre-equipped indoor areas.
Remembering or figuring out the parking location of the vehicle, for example the car, is not always easy especially when the size of the related parking lot or area is big or unfamiliar. It is very useful to know where a user has parked his/her vehicle, for example a car, such that the user could easily find it later on when coming back to the parking, for example when the user leaves his office after a long day at work and he does not want to spend any extra minutes just to remember or to figure out where has he parked his car.
When parking in uncovered outdoor parking lot the user might use any GPS application to record the GPS coordinates of the location where the car has been parked, and later on the user just use any navigation system to navigate back to his car's location. But unfortunately sometimes the user forgets to manually record or trigger the recording of the location of his car, and later on when he return back to the parking it would be not easy to find his car as he has not saved its parking location. Therefore, saving the parking location manually might work only and only if the user remembers to do it, but this is not always possible with human being.
Some solutions use the change in the movement profile to automatically detect the location where the car has been parked. For example, based on the movement speed, when the speed is higher than a certain threshold the system understands that the user is driving, and when the speed drops below a certain threshold the system understands that the user is walking. The location where the transition from driving to walking happened corresponds to the location where and time when the car has been parked. Such a solution cannot work in covered areas (e.g. underground parking) due to the unavailability of GPS, and where indoor localization is enabled by technologies that cannot offer the same accuracy as GPS which is needed to clearly distinguish the user movement profile (walking or driving).
Alternatively, some state of the art parking management systems provide a camera-based solution that enables the user with an interface to figure out in which zone or area of the parking lot a specific car has been parked. Such solutions work fine in both indoor and outdoor parking, but they require the installation of several cameras (i.e. at the entries and exits of each zone or area of the parking lot), which can be too costly.
Furthermore, when an incident e.g. a fire takes place in a closed indoor environment which is not already equipped with a system that enables indoor localization, the rescue team faces a real challenge to move inside that environment in an efficient and optimal way especially when the visibility is reduced for example due to dark smokes. And sometimes the rescue agents take the risk to go and move inside such strange environments with the risk that they cannot find their way back to the exit, which might end up sadly with death or serious consequences especially when the agents life depends on the amount of oxygen available inside the oxygen bottle and thus depends on the time they spend to get back to the exit.
In view of the disadvantages inherent in the conventional means of indoor localization of targeted smart objects and their users, it has remained a constant concern to provide for more practical, more efficient cost effective means to enable the identification of a targeted smart object and the user holding the targeted object inside a moving entity based on the orientation of the object to be localized as well as automatic detection and calculation of the time and location when and where the vehicle has been parked.